Dataset contains 11 clinical features for predicting heart disease events.

This project helps to predict whether the patient has Heart Disease or not. This prediction is made using the clinical data of patients.

Dataset Discription
Attribute	Description
Age	Age of a patient [years]
Sex	Gender of the patient [M: Male, F: Female]
ChestPain	Chest pain type [TA: Typical Angina, ATA: Atypical Angina, NAP: Non-Anginal Pain, ASY: Asymptomatic]
RestingBP	Blood pressure in Hg (Normal blood pressure - 120/80 Hg)
Cholesterol	Serum cholestrol level in blood (Normal cholesterol level below for adults 200mg/dL)
FastingBS	Fasting Blood Sugar (Normal less than 100mg/dL for non diabetes for diabetes 100-125mg/dL)
RestingECG	Resting electrocardiogram results [Normal: Normal, ST: having ST-T wave abnormality (T wave inversions and/or ST elevation or depression of > 0.05 mV), LVH: showing probable or definite left ventricular hypertrophy by Estes' criteria]
MaxHR	Maximum heart rate achieved [Numeric value between 60 and 202]
ExerciseAngina	Exercise-induced angina [Y: Yes, N: No]
Oldpeak	oldpeak = ST [Numeric value measured in depression]
ST_Slope	The slope of the peak exercise ST segment [Up: upsloping, Flat: flat, Down: downsloping]
HeartDisease	output class [1: heart disease, 0: Normal]